Cell motility is a key factor in progression from a benign neoplasm to invasion and metastasis. It is therefore important to understand 1) how cell motility affects spatial structure and 2) how previously sedentary neoplastic cells acquire the cancer phenotype of motility. Current methods cannot detect neoplastic cell motility in vivo in humans. Further, it has been difficult to develop interventions to prevent cell motility, because the pressures that select for the evolution of cell motility are poorly understood. Here, we use agent-based modeling and techniques adopted from ecological and evolutionary theory (such as phylogeographic analysis) to generate methods for estimating the presence of motile cells based on genetic and epigenetic data from biopsies. We will also test in silico whether local resource depletion can promote the evolution of cell motility. Our first aim is to develop statistical techniques for detecting the presence of unconditionally motile and conditionally motile cells in simulated tissues. We will then use this framework to test the power of various biopsy procedures to detect motile cells before metastasis has occurred. We will use data from colorectal neoplasms and Barrett's esophagus to test our techniques for estimating cell motility. Our final aim is to explore the selective pressures leading to the evolution of cell motility, in particular how degradation of local resource microenvironments leads to the evolution and emergence of motility. We will also test the viability of proposed interventions targeted towards reducing the selective and environmental pressures that promote cell motility. The successful completion of aims 1 and 2 will generate biopsy protocols to enable the early detection of cell motility before metastasis has occurred. Our final aim will generate hypotheses for novel interventions that can reduce selection for motile cells and thereby reduce the risk of metastasis. These projects will contribute to the goals of detecting precursors of malignancy and reducing the likelihood that a neoplasm will progress to invasion and metastasis. The emergence of cells that move through tissues is a necessary precursor to the colonization of cancer throughout our bodies and the transformation of a benign tumor into a malignant tumor. Here we create computational simulations that enable us to study the spatial and genetic patterns generated by the movement of cells in a benign tumor, as well as the evolutionary forces selection for cell movement in the tumor. The results of these simulations should enable the development of more effective methods for the early detection of cancer and innovative interventions that prevent the evolution of malignancy.